California State Health Assessment Core Module 2024 Update
Reporting data through 2022
Introduction
This annual State Health Assessment (SHA) Core Module provides a snapshot of the health status for the entire California population. The module is based upon a set of standard inputs, produced using an automated system, to assess population health across a range of health conditions, demographic characteristics, and other factors (e.g., disparities and inequities). The module is used to identify key findings that contribute to informing the State Health Improvement Plan.A range of data are used in this Core Module including data on deaths, hospitalizations, reportable diseases, emergency department visits, years lived with disability, social determinants of health, and population denominator sizes. Multiple types of data are essential for describing the state of health of the California population.
A majority of the charts and tables in this module are based on death data. Death data are a high quality, geographically and demographically granular, and consistent data source. Death data allow for objective comparisons over time and between groups, using a solid indicator of a hard outcome. The California Burden of Disease Condition List allows for investigation on a wide range of causes of death grouped into conditions related to clear clinical and public health programmatic areas.
There are certainly many conditions that have tremendous population health impact, such as mental health conditions, back and neck pain, and multiple sclerosis, which do not directly cause death. These are addressed to the degree possible with other measures (e.g., hospitalization, years lived with disability). There are also some very commonly occurring conditions, like sexually transmitted diseases, which rarely cause death or disability—some of these are reflected in the measure of reportable diseases.
As a key annual milestone in the ongoing State Health Assessment process, the Core Module provides a standard set of measures for comparative analysis. While maintaining this consistency, enhancements are incorporated each year along with relevant data sources as they become available. Additional detail and tools for further exploration of data are available through the California Community Burden of Disease Engine (CCB), the State of Public Health Report, and the Let’s Get Healthy California website.
A couple of key definitions and notes regarding conventions and interpretation of the data:
- All rates are per 100,000 population
- All rates are age-adjusted unless otherwise noted
- All data are for the state of California, except where noted for California counties or regions
- “All-cause” death rates (or numbers) refer to total from all causes of death combined. “Cause-specific” death rate (or number) refers to death from just one specific condition
Additional detailed information including definitions of many other terms in this document (e.g., “Years of Life Lost”), methods, and data sources, can be found in the Technical Notes section of this Core Module and in the technical notes section of the CCB. Additional data, including specific numbers and rates, for almost all death, hospitalization, and emergency department data in the Core Module can be found in the CCB. For comments, questions, or suggestions regarding this Core Module please email ccb@cdph.ca.gov.
1 Overall State of Health and Big Trends
1.1 Life Expectancy Summary for 2022 - By Race and Ethnicity and Sex
Life expectancy is a key summary measure of disparity, and succinctly summarizes differences in mortality between groups.
This chart shows Life Expectancy at Birth in 2022 for males and females, for each race and ethnic group. Calculation of life expectancy is complex, and requires use of assumptions applied to high-quality data.For all race and ethnic groups, females live longer than males. Among males, the life expectancy for Black males is 12.0 years less than for Asian males; among females the difference is 10.1 years. This difference is caused by a cascade of inequities in social determinants of health, and other systemic factors.
The red slashes at the bottom of the y-axis indicate that the scale of the y-axis is discontinuous. The y-axis does not start at 0, but rather at age 65, so that the important differences in life expectancy can be seen clearly.
1.2 Life Expectancy by Race and Ethnicity and Sex, by Year, 2000 to 2022
This chart shows the trends in Life Expectancy at Birth for the past 23 years by sex and race and ethnicity.
Life expectancy steadily increased for all groups over this period, until 2020. In 2020 there was a sharp drop for all groups due to the impact of COVID-19. From 2020 to 2021, life expectancy continued to decrease, albeit less sharply, for males of all race and ethnic groups, and for Latina females. Life expectancy increased in 2021 for Asian and Black females, and just slightly for White females. In 2022, life expectancy increased for all groups, most significantly among Latino males and females.
Black males have had a substantially lower, and Asian females a substantially higher, life expectancy than all other groups in all years.
1.3a All-Cause Mortality Trend (2000-2022) by Race and Ethnicity and by Sex, and All-Cause Mortality County Rankings (2022)
The line charts show the trends in age-adjusted rate for mortality due to all causes, by race and ethnicity and by sex for the past 23 years. In a simple sense, all-cause mortality is the opposite of life expectancy—when all-cause mortality goes down, life expectancy goes up, and vice versa.
The bar chart displays county rates of age-adjusted mortality (and 95% confidence intervals) due to all causes. The counties listed have the highest rates, and a reference line is included for comparison with the state rate.The “Trends by Race and Ethnicity” chart demonstrates that all-cause mortality rates decreased substantially (between 18 and 25 percent) among all race and ethnicity groups in California from 2000 to 2019.
Starting around 2013-2015, mortality rates started to level off and even increase for all groups except for White individuals.
Rates then increased sharply for all groups in 2020, although much less so for White individuals. In 2021, rates continued to increase sharply for Native Hawaiian/Pacific Islander (NHPI) and American Indian and Alaska Native (AIAN) populations, and increased slightly for Latino, White, and Asian populations. In 2021, rates decreased slightly for Black individuals from the peak in 2020.
In 2022, rates decreased among all racial and ethnic groups. NHPI, AIAN, and Latino populations had the largest decreases.
The very sharp and unprecedented increase among Latino individuals resulted in their all-cause death rate being higher in 2020 than any point in the past 20 years and, for the first time, higher than the rate among White individuals. The Latino population rate remained higher than the White rate in 2021, and then decreased to be lower than the White rate in 2022.
The “Trend by Sex” chart shows that all-cause mortality rates decreased for both males and females over the 20-year period, until 2020. Males consistently had a higher all-cause mortality rate than females.
1.3b All-Cause Mortality Map - California, Bay Area, and Los Angeles County, 2018-2022
These maps display all-cause mortality rates by location: statewide and regional views for the Bay Area and Los Angeles county (since these two regions include large urban cores with dense populations). The rates are compared at the subcounty level using Medical Service Study Areas (MSSAs), an aggregation of census tracts, to demonstrate variation between communities within each county.
There are concentrations of high all-cause mortality rates within all counties and regions.
There are some concentrations of higher rates in the central part of the State.
2 Rankings of Leading Causes
2.1 Multiple Lenses - Top 5 Conditions based on Multiple Measures
This multi-chart emphasizes that there are many ways to view the health status of Californians. Public health looks across multiple measures to identify public health challenges.
The first four charts use measures relating to deaths (number, years of life lost (YLL), increase, and race and ethnicity disparity). The next four charts look at additional lenses of public health burden (hospitalizations, emergency department (ED) visits, reportable diseases, and disability). Definitions of these measures can be found in the technical notes section below. Local Health Jurisdiction-level versions of this same multi-chart and a downloadable document can be found here. Additional complete data is available for LHJs upon request.Many conditions appear on more than one of these ranking measures, even though the measures assess very different levels of burden or impact:
In 2022, ischemic heart disease was the top cause for total number of deaths and a leading cause for YLL (3rd). While much ameliorated compared to 2021, COVID-19 remained the fourth leading cause for both the total number of deaths and ED visits.
Drug overdose saw by far the largest increase in death rates from 2012 to 2022. It was also the highest in YLL.
Alcohol-related conditions are a leading cause for YLL (4th), increase in death rates (4th), and racial and ethnic disparity (4th).
Mental health conditions are a leading cause for numbers of hospitalizations (3rd) and YLDs (2nd).
Additional details on key findings for these measures are provided in later sections.
COVID-19 is excluded as a cause in comparisons that involve years before the COVID-19 pandemic.
*Conditions with fewer than 100 deaths in either period are excluded. Such conditions with large percent increases include:
Influenza: 469.5% increase in age-adjusted death rate from 2012 (71 deaths) to 2022 (515 deaths)
Respiratory failure: 142.2% increase in age-adjusted death rate from 2012 (71 deaths) to 2022 (228 deaths)**The most recent year of data for STDs is 2020, for TB 2021, for vaccine preventable diseases 2020, and for other reportable infectious diseases 2021.
***2019 is the most recent year these data from the Institute for Health Metrics and Evaluation are available.
2.2 Broad Condition Groups (6) - Rankings of Number of Deaths and Years of Life Lost in 2022
This set of charts compares all causes of death using six broad condition groupings. These broad groupings are important for a very high-level understanding of the burden of death and disease, and these groupings (indicated by color) are used to frame the data in many of the charts that follow.
The top chart ranks the number of deaths in California in 2022 according to the six broad condition groupings. The bottom chart shows the ranking of YLL according to the six broad condition groupings. YLL weights conditions that impact younger people and is sometimes referred to as “premature death”.Cardiovascular diseases caused the most deaths in 2022, followed closely by Other Chronic diseases. The Cardiovascular diseases broad condition group includes ischemic heart disease, stroke, hypertensive heart disease, and others. The Other Chronic disease broad condition grouping includes Alzheimer’s disease, Chronic Obstructive Pulmonary Disease (COPD), kidney disease, and others.
Injuries caused by far the most years of life lost in 2022. This broad condition group includes drug overdose, alcohol-related conditions (including alcohol-related cirrhosis), suicide, homicide, falls, and road injury.
2.3 Public Health Condition Groupings - Top 15 Number of Deaths in 2022
These charts show a more detailed view of causes, disaggregated into what we call the Public Health Level groupings. This grouping is based on programmatic areas of public health and/or clinical aspects of the conditions to facilitate public health planning and action.
This chart shows the ranking of the top 15 causes based on numbers of deaths.At this Public Health Level, the conditions contributing the most deaths are ischemic heart disease, Alzheimer’s disease, and stroke. Note that three of the top five leading causes of death are in the Cardiovascular broad group.
COVID-19 is the fourth leading cause of death, and the only cause in the Communicable disease broad condition group which is ranked in the top 15 causes based on number of deaths.
2.4 Public Health Condition Groupings - Top 15 Years of Life Lost in 2022
This chart shows the ranking of the top 15 Public Health Level causes for years of life lost.
The leading contributors to years of life lost are drug overdose, road injury, and ischemic heart disease. Note that five of the top seven leading causes of years of life lost are in the Injury broad grouping.
In 2019, drug overdose deaths overtook ischemic heart disease as the top cause of years of life lost. This was the first time any cause ranked higher than ischemic heart disease for at least two decades. In 2020, drug overdose continued to rank higher than ischemic heart disease, but in 2021 COVID-19 was the top cause (1st). Drug overdose became the top cause of years of life lost again in 2022. Beginning in 2022 road injury also ranked higher (2nd) than Ischemic heart disease. Due to the magnitude of deaths from ischemic heart disease, it has been a leading cause both in terms of number of deaths and years of life lost for the past 20 years.
2.5 Public Health Condition Groupings - Top 15 based on Percent Increases in Age-Adjusted Death Rates in Different Periods
This multi-chart shows the ranking of the top 15 Public Health Level causes based on percent increase in rates across several periods. The first two charts present increases in the “pre-pandemic period” for the greatest ten year increases from 2009 to 2019, and the greatest five year increases from 2014 to 2019. The next set of charts presents increases during the COVID-19 pandemic period beginning with the two year increases from 2019 to 2021 and then the most recent single year increases from 2021 to 2022. A detailed data table with these increases is included in Appendix A.1.
Deaths from drug overdoses increased more than any other condition both from 2009 to 2019 and 2014 to 2019; and continued to increase sharply from 2019 to 2021, second only to COVID-19. The increase in drug overdose deaths slowed significantly in 2022. It was not among the top 15 causes with the largest increases from 2021 to 2022.
Other than COVID-19 and drug overdoses, conditions that increased substantially in the pandemic period include obesity, homicide, alcohol-related, road injury, and poisonings (non-drug related). The very large increase in homicides between 2019 and 2021 is striking—except for COVID-19, drug overdoses, kidney disease, Parkinson’s disease, and obesity, this is the largest increase seen compared to any other conditions in any of these periods.
These recent increases are concerning and need further exploration, including their relationships to the pandemic. More detail and information related to increases in the pandemic period can be seen in the CDPH Excess Mortality Data Brief. Of note, several of these conditions that have increased are in the “deaths of despair” category. The term “deaths of despair” was introduced by Case and Deaton in 2015 (Case & Deaton, 2015), and has generated substantial attention as an area of increasing deaths needing focused public health attention. Per Case and Deaton, “deaths of despair” include drug overdoses, suicides, and deaths due to alcoholic liver disease. Several behavioral health related conditions in this category may be influenced by interrelated drivers including stress and substance use. In their original work, the authors noted higher rates among younger, less educated White populations. In California, the deaths of despair due to drug overdoses are very high and increasing among younger and middle-aged AIAN, Black, White, and NHPI populations.
Other conditions that increased substantially in the pre-pandemic periods include kidney disease, Parkinson’s disease, congestive heart failure, other neurological conditions, hypertensive heart disease, Alzheimer’s disease and road injury.
The extremely large increase in kidney disease in the pre-pandemic period is striking. The specific reasons for this increase are not clear but are being investigated and warrant further investigation.
Note: Conditions with fewer than 100 deaths in all time periods are excluded.
2.6 Public Health Condition Groupings - Top 15 based on 10-year Percent Decreases in Age-Adjusted Death Rates, 2012 to 2022
This chart shows the ranking of the top 15 Public Health Level causes based on percent decrease in rates from 2012 to 2022.
Deaths from hepatitis decreased more than 60% over this 10-year time period. This decrease is likely due in large part to the tremendous advances in treating hepatitis C, and to a range of public health efforts.
Decreases from other conditions, like lung cancer, are also likely due to well-documented public health efforts. Many other decreases warrant further investigation.
*Conditions with fewer than 100 deaths in either period are excluded. Such conditions with large percent decreases include:
Meningitis: 46.76% decrease in age-adjusted death rate from 2012 (86 deaths) to 2022 (50 deaths)
ARDS: 30.01% decrease in age-adjusted death rate from 2012 (65 deaths) to 2022 (57 deaths)
3 Trends in Deaths
3.1 Trends in Broad Condition Groups - Age-Adjusted Death Rate, 2000-2022
This chart shows the age-adjusted death rate trends of the six broad condition groupings in California from 2000-2022.
Great progress has been made in the past 20 years, through 2019, with decreasing death rates for Cardiovascular disease, Cancer, and Communicable disease. In contrast, death rates for Other Chronic diseases and Injury increased somewhat over this period. The increase in Other Chronic diseases is due in large part to increases in deaths from Alzheimer’s disease.
In 2020 and 2021, deaths increased very sharply for Communicable diseases due to COVID-19; and increased for Injury in both years. Deaths due to Communicable diseases decreased sharply in 2022, while Injury deaths decreased slightly. Deaths from Cancer continued the encouraging downward trend of the prior 20 years through 2022.
3.2 Trends In Top Public Health Conditions (by Broad Condition Groups), 2000-2022
These charts provide a deeper look into the trends in cause of death by showing the age-adjusted death rate trends of the top 5 Public Health conditions within each broad condition group.
The previous chart showed good progress within the Cardiovascular and Cancer broad condition groups during the past couple of decades. These more detailed charts reveal the main drivers for those two downward trends, which are ischemic heart disease and lung cancer. (Ischemic heart disease decreased every year from 2000 to 2022, except for the slight increase in 2020. The reason for this reversal in trend in 2020 is not known and warrants investigation.) Furthermore, pneumonia deaths from the Communicable group also greatly declined since 2000. In contrast, Alzheimer’s disease in the Other Chronic group and drug overdoses in the Injury group have sharply increased since 2000.
The increase in Alzheimer’s disease appears to be driving the observed increase in the broader Other Chronic group. In contrast, chronic obstructive pulmonary disease (COPD) deaths have decreased substantially (but remain a leading cause of death).
In the Injury broad condition group, drug overdoses have more than quadrupled, and road injury is increasing after a previous decline. Alcohol-related deaths increased sharply in 2020 and again in 2021, but decreased in 2022. Homicides, after many years of decreasing or level rates, increased sharply in 2020, and increased again in 2021, but decreased in 2022.
In the Perinatal condition group, deaths due to neonatal conditions declined significantly since 2000, and reached their lowest level in 2020, but increased in both 2021 and 2022.
Note: The y-axis scales for each chart are different.
3.3 Trends in Age-Adjusted Rates for Top 15 Public Health Level Conditions (log-y-axis), 2000-2022
This chart offers a different perspective than the previous charts by looking at trends over the past two decades for public health-level conditions overall, regardless of the broader groups. These are the conditions with the top 15 age-adjusted death rates in 2022.
Age-adjusted death rates from ischemic heart disease, stroke, lung cancer and COPD decreased greatly over the past 20 years.
This very encouraging decrease in ischemic heart disease is likely due to increasing use of statins for treatment of high cholesterol, and due to prevention behaviors related to healthier nutrition and exercise. The substantial decrease in lung cancer is very likely due to decades-long widespread State and National tobacco control efforts. In contrast, Alzheimer’s disease has more than doubled since 2000, resulting in it having the second-highest rate from 2008 onward (except third highest in 2020 and 2021 because of COVID-19).
Also of note are drug overdoses and kidney diseases. While these conditions are lower on the list, their age-adjusted death rates have increased dramatically since 2000.
A logarithmic scale is used for the y-axis in order to be able to clearly see the trends for all these conditions on one chart. Also, on a logarithmic scale, lines are parallel if the relative changes (i.e., percent change) over a time period are the same.
4 Preliminary Data - 2023
4.1 2023 Preliminary Data: Top 5 Causes of Death and Years of Life Lost
This chart shows leading causes of death and the leading causes of Years of Life Lost (YLL) in 2023.
Ischemic heart disease was the leading cause of death (1st) and a leading cause of YLL (2nd) in 2023; Alzheimer’s disease was a leading cause of death (2nd). Drug overdoses were the leading cause of YLL (1st) in 2023. Stroke was a leading cause of death (3rd) and road injury was a leading cause of YLL (3rd).
5 Detailed Focus on Age and Race and Ethnicity
5.1 Race and Ethnicity Age-Specific All-Cause Death Rate Ratio with White Population as Reference Group, 2020-2022
This chart shows the ratio of age-specific AIAN, Asian, Black, Latino, and NHPI population rates to the corresponding age-specific White population rates (White individuals are used as the reference group since they have historically been the one of the largest groups in the State, and are, on average, relatively advantaged).
A rate ratio of 1.0 means that the rates are the same for both groups.
Appendix Table A.2 shows the numbers of deaths and rates that are the basis for the rate ratios in the chart.Of the many observations that can be seen in this chart, one especially important observation is seen in the “Black:White” rate ratio column. In the 0-4 year old age group, the death rate is over 3 times higher for Black infants/toddlers than for White infants/toddlers. For children/teens/early 20’s and 35-44 age group, the rates are over 2 times higher for Black populations than White populations. In general, this disparity is greater at younger ages and the ratio decreases as age increases. Among the oldest age group, the rate among Black individuals is slightly less than the rate among White individuals. This difference likely reflects the outcome of disparities in death rates earlier in the life course (with more deaths among the Black population at younger ages), leaving only a smaller number of relatively healthy Black people in the oldest age group.
Many complex factors interweave to create these disparities and patterns. The much higher rates of death among the Black population across most age groups are due in large part to the cascade of social determinants of health (e.g., discrimination/racism, poverty/wealth) and historical and structural inequities (e.g., housing, education, employment) that impact health and life expectancy.
Among the Latino population, rates are better (lower) than, or very similar to, White individuals ages 25 and older, but worse (higher) between ages 0 and 24, with the greatest difference at the youngest (0-4) age level.
Among AIAN and NHPI individuals, the patterns are similar to the pattern described for Black individuals, and important for the same reasons. Because of the much smaller population sizes of these two groups, there is more variability in the numbers.
Among Asian individuals, the rates of death are lower than the rates among White individuals. However, the overall low rates likely mask differences between different Asian subgroups, as noted in Section 9.3 below.
*Data are suppressed per the California Health and Human Services Agency Data De-Identification Guidelines
The black line at the end of each bar is the 95% confidence interval for the rate ratio, calculated with the rate ratio function of the epitools package in R.
5.2 Change in Race and Ethnicity All-Cause Mortality Rate Disparity, 2000-2022
This chart presents information on trends in all-cause mortality by race using rate ratios.
This chart shows changes over time in the rate ratio of the other race and ethnic groups compared to White populations. It shows increasing differences from the White population rate for all groups starting in the early to mid-2010s, with a sharp acceleration in these disparities in 2020 due to the impact of COVID-19. In 2021, this sharp acceleration continued for NHPI and AIAN populations, leveled off for Latino populations, and decreased slightly for Black and Asian populations. The disparities between other race and ethnic groups and the White population decreased in 2022, especially among NHPI, AIAN, and Latino populations. (The chart in section 1.3a serves as important background for this chart.)
5.3 Ranking of Race and Ethnic Disparities in Death Rate, 2020-2022
This chart ranks causes of death by racial and ethnic disparities. Disparities are measured using rate ratios, comparing the rate among the race and ethnic group with the highest rate to the rate among the race and ethnic group with the lowest rate for each cause of death. Data for 2020-2022 are combined for statistical stability.
A rate ratio near one means there is little difference between the groups with the highest and lowest rates. The bar size shows the rate ratio; the labels inside the bar show the group with the highest rate and the lowest rate (highest:lowest) for that cause.
Appendix Table A.3 shows the numbers of deaths and rates that are the basis for the rate ratios in the chart.The top disparity in death rates is for obesity (1st), with the NH/PI population rate almost 22 times the rate among the group with the lowest rate (Asian population).
Homicide has the second highest disparity (2nd), with the Black population rate more than 16 times the rate among the Asian population.
Another leading disparity is for HIV/STD (3rd), where the Black population rate is about 13 times higher than the Asian population rate.
The next leading disparity, alcohol-related conditions (4th; 13 times), and another leading disparity, drug overdoses (6th; 10 times), both have the highest rates among AIAN individuals and the lowest rate among Asian individuals.
An additional leading disparity is for tuberculosis (5th), with the Asian population rate more than 11 times higher than the rate among White individuals. (The high rate among Asian individuals in California is known to be associated with persons born outside of the United States. Report on Tuberculosis in California, 2019).
5.4a Top Ranking Causes by Crude Death Rate, 2020-2022
The charts shown in sections 5.4a, 5.4b and 5.4c look at deaths, hospitalizations, and ED visit data by race and ethnicity; showing all race groups, with the ranks sorted based on one selected race group.
The same charts, for all age groups and all California counties are also available in the California Community Burden of Disease Engine (CCB) in the “Ranks” section, in the “AGE RACE FOCUS” Tab.
Additionally, information about disaggregated race and ethnicity groups is available in section 9.3.This chart is for deaths, ordered based on rates among AIAN individuals, and indicates that the leading causes of deaths among AIAN individuals include drug overdoses (3rd) and alcohol-related conditions (4th). These two causes of death do not rank among the top five causes of death for any other race and ethnic group (except drug overdose deaths are 5th for Latinos).
5.4b Top Ranking Causes by Crude Hospitalization Rate, 2020-2022
- This chart is for Hospitalizations, ordered based on rates among Black individuals, and indicates that the leading causes of hospitalization for Black individuals are septicemia (1st) and mental health related causes (3rd and 5th).
The chart indicates that this is not the same ordering for all other race and ethnic groups. For example, among both Asian and Latino populations, “other complications of birth” is the second leading cause of hospitalization, which is only the ninth leading cause among Black populations.
5.4c Top Ranking Causes by Crude Emergency Department Rate, 2020-2022
- This chart is for Emergency Visits ordered based on rates among Black individuals, and indicates that for all race and ethnic groups, abdominal pain, chest pain, and upper respiratory infections are leading causes for ED visits.
The chart also shows that the rates of ED visits for many conditions are higher among Black persons than other groups. These differences are likely due to many factors, including reduced access to health care services leading to increased use of ED for primary care among Black populations, and a cascade of many other factors, leading to a higher incidence of many of these conditions.
5.5 Trends in Mortality Rates and Percent Change in Mortality by Age Group from 2010 to 2022
Chart (i) shows age-specific trends in mortality rates by age group from 2010 to 2022. Chart (ii) shows percent changes in mortality rates by age group from 2010 to 2019 (pre-pandemic period), 2019 to 2021 (pandemic period), and 2021 to 2022 (recovery period).
25-34 age group, where rates increased steadily and strongly; and for the 35-44 age group, where rates increased somewhat.
From 2019 to 2020, due to COVID-19, rates increased for all groups (except infants/toddlers). From 2020 to 2021, rates continued to increase sharply for the 25-34 and 35-44 year old age groups. For some other age groups, the rates also continued to increase, and for others they leveled off or decreased. From 2021 to 2022, rates decreased among all but the two youngest age groups, 0-4 and 5-14.
Over the pre-pandemic period from 2010 to 2019, the rate increased 52% among the 25-34 year age group, 14% among the 35-44 year age group, and decreased among all other groups.
The percent change in mortality rate by age group during the pandemic period (2019 to 2021) increased for all age groups (except for infants/toddlers); with the largest increases being among younger adults (25-34 and 35-44) at 50% and 61% respectively.
The percent change in mortality rate by age group during the recovery period (2021 to 2022) decreased for all age groups except for infants/toddlers and 5-14 year age group; with the largest decreases being among the 45-54 and 55-64 age groups at 17% and 16%.
5.6 Leading Causes of Death Across the Life Course, 2020-2022
This chart shows the five leading causes of deaths across the “life course” for each age group. The chart shows the rank, the number of deaths, and is color coded for the broad condition group for each cause of death. This same chart, with additional stratification by sex and race and ethnicity, is available for all local health jurisdictions here.
As expected, the number of deaths are much larger among the older age groups than the younger groups.
The youngest age group 0-4 is most impacted by neonatal conditions and congenital anomalies.
From 15-24 to 35-44, the leading causes of death are mostly injury-related, such as deaths due to drug overdoses, road injuries (also the leading cause among 5-14), suicide/self-harm, etc. Drug overdose is the leading cause of death between the ages of 15 and 44.
Ischemic heart disease starts to appear as a leading cause in the 45-54 age group and becomes the leading cause of death among Californians between the ages of 65 to 84.
Breast cancer (among females) appears as one of the leading causes in the 45-54 and 55-64 age groups.
Lung cancer appears as one of the leading causes of death between the ages of 65 to 74.
The top cause of death among the oldest Californians (85+) is Alzheimer’s disease.
In general, this “life course” chart shows a progression from multiple causes in the youngest age groups, to Injury causes in middle age groups, to Cardiovascular, Cancer, and Other Chronic diseases in older age groups; in addition to COVID-19 in middle and older age groups in the pandemic period.
5.7a Top Ranking Causes of Deaths, Hospitalization, and ED Visits, Age 15-24, 2020-2022
The charts in sections in 5.7a, 5.7b, and 5.7c show the leading causes of deaths, hospitalizations, and ED visits for a selected age group at different stages of the life course (starting with the 15-24 age group) using data from 2020 to 2022 combined.
These age groups have been selected to highlight different patterns in causes of deaths, hospitalizations, and ED visits at each stage.
Additional age groups, race and ethnicity, and county level views for these same ranked data can be seen in the California Community Burden of Disease Engine (CCB) in the “Ranks” section, in the “DEATH HOSP ED” Tab.This first chart is for the 15-24 years age group, and shows that five of the top six leading causes of death, and many of the top causes of ED visits, are injury-related. The top causes of hospitalization are mental health and perinatal-related. Drug overdoses, road injury, homicide, and suicide are by far the leading causes of death in this age group.
5.7b Top Ranking Causes of Deaths, Hospitalization, and ED Visits, Age 45-54 , 2020-2022
- This next chart is for the 45-54 years age group, and shows that 1) the leading causes of death include COVID-19, injury (in particular drug overdoses and alcohol-related), and cardiovascular; 2) the leading cause of hospitalization in this group (and in many of the older age-groups) is septicemia, followed by COVID-19 and schizophrenia; and 3) ED visits are due to a wide range of conditions.
5.7c Top Ranking Causes of Deaths, Hospitalization, and ED Visits, Age 85+, 2020-2022
- This third chart is for the 85+ years age group and indicates that between 2020 and 2022, Alzheimer’s disease is the leading cause of death followed by Cardiovascular diseases (four of the next five leading causes), and COVID-19.
Septicemia is the leading cause of hospitalization; other leading causes include Cardiovascular diseases and fractures.
Urinary tract infections are a leading cause of ED visits (2nd); three of the five leading causes, including the top cause, are Injuries.
6 Years Lived with Disability and Disability Adjusted Life Years
These charts present information about conditions associated with Years Lived with Disability (YLDs) and risk factors associated with Disability-Adjusted Life Years (DALYs). They are based on complex model estimates from the Institute for Health Metrics and Evaluation. They provide information for prioritizing public health resources and action based on assessing the prevalence of a wide range of environmental and behavioral risk factors, and the associations of these factors with specific conditions.
The most recent data available are from 2019. All rates shown are the respective value (YLDs or DALYs) per 100,000 population.
6.1 Conditions associated with Years Lived with Disability
The YLD measure accounts for the number of years lived with an illness or health condition and the severity of the condition throughout life.
These charts show: a) the top 10 causes associated with the greatest number of YLDs in 2009 and in 2019; and b) the top causes by selected age groups in 2019.
6.1a Ranking of Conditions based on Associated Rate of Years Lived with Disability, 2009 and 2019
- The top cause associated with the greatest number of YLDs spanning a decade is musculoskeletal disorders (e.g., low back pain, neck pain, and others), followed by mental disorders. While the top four leading causes of disability have not changed between 2009 and 2019, diabetes and kidney diseases increased in rank (from 7th in 2009 to 5th in 2019), and unintentional injuries were not included in the top 10 in 2009 but were the ninth leading cause (9th) in 2019.
6.1b Ranking of Conditions based on Associated Years Lived with Disability, by Selected Age Groups, 2019
- Musculoskeletal disorders were among the top five leading causes of YLDs in all groups, and the leading cause in 15-49 and 70+ year olds. Mental disorders were the leading cause of YLDs among the 5-14 group and the second leading cause in the 15-49 group.
Skin and subcutaneous diseases were the second leading cause, and chronic respiratory diseases the third leading cause of YLDs for the 5-14 year old age group.
Substance use disorders were the third leading cause of YLDs in the 15-49 year old age group. In the 70+ year old age group, sense organ disease was the second, and cardiovascular diseases the third leading cause of YLDs.
6.2 Risks Associated with Disability Adjusted Life Years
Disability-Adjusted Life Years (DALYs) are defined as the sum of years of life lost (YLLs) due to premature mortality and the years lived with disability (YLDs). DALYs are one important way to assess the degree of health burden associated with health risks.
These charts show the top 10 risk factors associated with the greatest magnitude of DALYs: a) in 2009 and in 2019; and b) by selected age groups in 2019.
6.2a Ranking of Risk Factors based on Associated Disability Adjusted Life Years, 2009 and 2019
- Four of the six leading risk factors in 2009 and 2019 for the highest number of DALYs are related to diet and exercise, and other factors associated with obesity and high blood pressure. Three of the top ten leading risk factors relate to substance use (i.e., alcohol, tobacco, and other drugs).
Between 2009 and 2019, the leading risk factor for DALYs shifted from tobacco use to high body-mass index.
6.2b Ranking of Risk Factors based on Associated Disability Adjusted Life Years, by Selected Age Groups, 2019
The leading risk factors associated with DALYs in the 5-14 year old age group were child and maternal malnutrition, followed by childhood sexual abuse and bullying. Three of the leading risks in this age group were associated with nutrition, three with substance use, and two with the environment.
In the 15-49 year old age group, three of the leading risk factors for the highest number of DALYs—including the top risk factor—related to substance use; and half of the leading risk factors related to healthy eating, exercise, and other factors associated with obesity and high blood pressure. Another leading risk factor was occupational risks (4th).
In the 70+ year old age group, half of the leading risk factors related to healthy eating, exercise, obesity, and high blood pressure. Two of the leading risk factors were alcohol and tobacco (but not other drug) use.
7 Additional Views for Selected Topics
- The following section provides a more thorough view on a select set of topics: ischemic heart disease, Alzheimer’s disease, drug overdose, road injury, obesity, and homicide. Information is presented on: the overall trend; differences across race and ethnicity, and age; as well as a ranking of the counties with the highest rates for the identified condition.
These topics were selected based on being among the leading causes for a particular measure: deaths, YLLs, increase in rates, or racial and ethnic disparities.
7.1 Ischemic heart disease
7.2 Alzheimer’s disease
7.3 Drug overdose
7.4 Road injury
7.5 Obesity
7.6 Homicide
9 Exploratory
9.1 Mental Health
This exploratory section examines mental health conditions. These conditions affect more than half of people in the United States over the course of their lifetime, one in five people every year, and are contributing factors to worse overall health.
Here, we have conducted analyses of emergency department visit and hospitalization rates for the broad mental health condition categories of: 1) anxiety and related disorders (including trauma and stressor-related disorders such as post-traumatic stress disorder), 2) mood disorders, 3) schizophrenia and related disorders, and 4) all other mental health conditions not fitting into one of these three other categories. These data were then grouped by race and ethnicity, and further by age for mood disorders and for schizophrenia, to examine if disparities in rates of ED visits and hospitalizations exist and for which age groups.
Compared with overall prevalence of mental health conditions, and the number of ED visits and hospitalizations, the number of deaths due specifically and directly to mental health is quite low. As currently grouped, there were 243 deaths from mental health-related conditions in 2022, but we do not include information about those data in this initial and exploratory section because of the small numbers and because we need further assessment and clinical input regarding the proper and optimal use of these codes.Taken together, these preliminary and exploratory data demonstrate a significant disparity in mental health conditions with Black populations having much higher rates of ED visits and hospitalizations for such conditions than other racial and ethnic groups.
Further, this disparity for Black populations is seen strikingly for almost all age groups, in particular among young people, as shown for ED visits for mood disorders and schizophrenia.
Understanding and addressing the issues underlying these disparities is both important and challenging. Some of the multiple and complex issues include inequities in access to mental health care and prevention services; the impact of bias and racism in the “labeling” and diagnosis and treatment of mental health problems by law enforcement, courts, educational systems, health care, and mental health professionals; as well as the potential impact of interrelated risk factors and social determinants of health (neighborhood disadvantage, community and family trauma, economic inequality) in the actual production of these mental health conditions through intensive exposures to trauma and toxic stress.
9.1a Hospitalizations and ED Visits for Broad Mental Health Conditions, 2022
This chart shows raw numbers of ED visits and hospitalizations for mental health-related conditions including anxiety and related disorders, mood disorders, schizophrenia and other related psychotic disorders, and other disorders.
Note that these data do not include some conditions associated with mental health including suicide/self-harm or accidental injury. Furthermore, developmental disorders, personality and behavioral disorders, physiological/physical behavioral syndromes, and physiologic-induced delirium are grouped into “Other” due to their overall small numbers.Anxiety and related disorders accounted for the highest number of ED visits, followed by schizophrenia and related disorders. Mood disorders accounted for the highest number of hospitalizations, followed by schizophrenia and related disorders.
9.1b Hospitalizations for Mental Health Conditions by Race and Ethnicity, 2022
This chart shows hospitalizations for mental health disorders grouped by race or ethnicity.
Schizophrenia was the leading cause of hospitalization for Black individuals, with a rate more than three times that of any other race or ethnicity, followed by mood disorders which also had a higher rate for Black individuals than for any other race or ethnicity.
Mood disorders were the leading cause of hospitalization for all races and ethnicities other than for Black individuals (for which it ranked second).
Asian individuals had the lowest rates of hospitalization for all mental health disorders relative to other races or ethnicities.
9.1c ED visits for Mental Health Conditions by Race and Ethnicity, 2022
This chart shows ED visits for mental health disorders grouped by race or ethnicity.
Schizophrenia was the leading cause of ED visits for Black individuals, with a rate more than three times that of any other race or ethnicity, followed by anxiety and related disorders then mood disorders, which both also had considerably higher rates for Black populations than for any other race or ethnicity.
Anxiety and related disorders were the leading cause of ED visits for all races and ethnicities other than Black populations.
Asian individuals had the lowest rates of ED visits for all mental health disorders relative to other races or ethnicities.
9.1d ED Visits for Mood Disorders by Race and Ethnicity and Age, 2022
This chart shows emergency department (ED) visits for mood disorders grouped by race or ethnicity and age.
ED visits for mood disorders were greatest for adolescents and young adults ages 15 to 24 for all races and ethnicities except for Black populations. Among Black people, the highest rate was in adults ages 25 to 34. However, ED visits for mood disorders were considerably higher for Black individuals across almost all age groups than for other races and ethnicities.
Although rates were lower among youth ages 5 to 14 compared to other age groups, Black youth had the highest rate of ED visits for mood disorders in this age group, consistent with the overall pattern seen.
Asian individuals had the lowest rates of ED visits for mood disorders relative to other races or ethnicities across almost all age groups.
9.2 Rural Health in California
- This exploratory section examines how an important dimension of the places in which people live, rural/urban categories, may impact their health. This section should be considered preliminary.
Rural/urban categories are an important concept related to health. Nationally, data demonstrate that rural populations experience comparatively worse health outcomes than the rest of the population overall. Rural risk factors include geographic isolation, lower socioeconomic status, higher rates of health risk behaviors, limited access to care, and many others (see Rural Health Disparities Overview - Rural Health Information Hub).
Rural/urban categories are defined in different ways by different systems. One system used by the Federal Health Resources and Services Administration (HRSA) are Rural-Urban Commuting Area (RUCA) codes based on the same concepts used by the Federal Office of Management and Budget (OMB) to define county-level urban and rural areas, but at the census tract level. These codes are on a 21-level continuum to account for varying levels of rural/urban categories across the full continuum (see USDA ERS - Rural-Urban Commuting Area Codes). We have collapsed these codes into seven category classifications for all census tracts in California as follows:
- Urban Core, Low Commuting - Urban 1.0: Metropolitan
- Urban Core, High Commuting - Urban 1.1: Metropolitan
- Urban Area, High Commuting - Urban 2.0: Metropolitan
- Urban Area, Low Commuting - Urban 3.0: Metropolitan
- Large Rural Area - Large Rural: Micropolitan
- Small Rural Area - Small Rural
- Isolated Rural Area - Isolated Rural
9.2a Table – Descriptive Data for Each Rural/Urban Category Grouping, 2022
- This table shows the number of census tracts, deaths, population, percent of statewide deaths, and percent of the statewide population for each of the seven rural/urban categories defined above using the RUCA coding system.
| RUCA | Number of Tracts | Area (Square Mile) | % Area | 2022 Deaths | Population | % of Statewide Deaths | % of Statewide Population | Age-Adjusted Death Rate |
|---|---|---|---|---|---|---|---|---|
| Urban Core, Low Commuting | 6,869 | 12,929 | 11.1% | 256,822 | 34,000,790 | 82.0% | 86.6% | 699.7 |
| Urban Core, High Commuting | 186 | 802 | 0.7% | 7,648 | 1,078,255 | 2.4% | 2.7% | 615.0 |
| Urban Area, High Commuting | 316 | 18,730 | 16.0% | 11,289 | 1,408,487 | 3.6% | 3.6% | 709.5 |
| Urban Area, Low Commuting | 51 | 3,804 | 3.3% | 2,209 | 276,763 | 0.7% | 0.7% | 750.0 |
| Large Rural Area | 289 | 22,082 | 18.9% | 14,131 | 1,423,503 | 4.5% | 3.6% | 811.7 |
| Small Rural Area | 76 | 13,189 | 11.3% | 3,575 | 371,812 | 1.1% | 0.9% | 796.3 |
| Isolated Rural Area | 125 | 43,520 | 37.2% | 3,816 | 357,608 | 1.2% | 0.9% | 725.8 |
| Missing Tract | NA | NA | NA | 13,010 | NA | 4.2% | NA | NA |
| CALIFORNIA | 8,057 | 116,840 | 100.0% | 313,231 | 39,283,497 | 99.8% | 99.1% | 732.8 |
9.2b Map of Rural/Urban Categories in California
This map shows each census tract in California by the seven rural/urban categories.
While most of California’s population resides in urban areas, much of the State’s land mass is made up of rural areas.
8 Social Determinants of Health and Place
Social determinants of health (SDOH) are the conditions in the environments where people are born, live, learn, work, play, worship, and age that affect a wide range of health, functioning, and quality-of-life outcomes and risks.
The six SDOHs included as examples are: 1) not voting (percent of registered voters that did not vote in the 2020 general election); 2) educational attainment (percent of population over 25 with high-school education or less); 3) housing burden (percent of renters and homeowners with housing costs exceeding 50% of income); 4) no extra income (percent of households with no interest, dividends, or net rental income in the past 12 months); 5) no health insurance coverage (percent of adults aged 19 to 64 currently without health insurance coverage);and 6) no internet access (percent of households without internet access).
The SDOH data are from the US Census Bureau’s American Community Survey (ACS), from 2015-2019. The data are aggregated into Medical Service Study Areas (MSSA) or counties. Note that these units of measurement are place-based, or geographic, rather than individual-based, and, especially for MSSA, allow the comparison of SDOH and health outcomes in the context of communities.
For Sections 8.1 and 8.3 the MSSA-level data is grouped into four levels (quartiles) from most advantaged (1) to least advantaged (4).
For more on SDOH see the CDPH Office of Health Equity’s “Demographic Report on Health and Mental Health Equity in California.”
8.1 Life Expectancy (Mean) by Quartiles of Selected SDOHs, 2018-2022
These charts show the mean (or average) community life expectancy based on quartiles of each social determinant.
Lower life expectancy is associated with lower rates of voting, education, housing affordability, extra income, health insurance coverage, and internet access.
The y-axis does not start at 0, but rather at age 70, so that the important differences in life expectancy can be seen clearly.
8.2 Communities with Highest and Lowest Life Expectancy, 2018-2022
This table shows the communities (MSSAs) with the 10 highest and lowest levels of life expectancy in the State. It also presents the mortality rate, percent did not vote, percent with educational attainment of high school graduation and below, percent with no extra income, percent with no internet access, percent without health insurance, and percent with housing burden, as well as overall population.
This tabular view of the data highlights the strong community-level associations seen above and emphasizes some extreme differences in life expectancy. Life expectancy in the least advantaged “Clearlake /Clearlake Oaks” community in Lake County at 70.0 is over 17 years less than the life expectancy of 87.4 in the most advantaged community of “Bel Air /Beverly Glen /Beverly Hills /etc.” in Los Angeles County.
8.3 Mean Age-Adjusted Cause-Specific Death Rate by Quartiles of Selected SDOHs, 2018-2022
These charts explore the relationships between social determinants of health (SDOH) and specific causes of death at the community (MSSA) level. Like the figure in section 8.1, each SDOH is divided into quartiles, with quartile 1 being the most advantaged and quartile 4 being the least advantaged. The four causes of death selected are: COVID-19, ischemic heart disease, suicide, and drug overdose.
Strong relationships are seen in COVID-19 and ischemic heart disease with almost all six of the SDOHs. In contrast, the patterns seen in suicide and drug overdose are less clear, as the least advantaged communities do not always have the highest death rate, and the most advantaged communities do not always have the lowest death rate.
8.4 County Level Social Determinants, Life Expectancy, and Death Rate for Selected Causes of Death, 2018-2022
With exceptions, this pattern is seen particularly in the northern and Central Valley portions of the State, both of which include more rural areas than other regions in the State.
Regions with the highest death rates for drug overdose and suicide are concentrated in the north with elevated rates throughout several additional rural areas, while the hot spots for COVID-19 and ischemic heart disease are more widely spread across the state.
*Data are suppressed per the California Health and Human Services Agency Data De-Identification Guidelines
For all maps, the color shading goes from lighter for more advantaged or better health outcomes, to darker for less advantaged or worse health outcomes.